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The study sought to evaluate a novel electronic health record (EHR) add-on application for chronic disease management that uses an integrated display to decrease user cognitive load, improve efficiency, and support clinical decision making.

The management and follow-up of diagnostic test results is a major patient safety concern. The aim of this qualitative study was to explore how clinicians manage test results on an everyday basis (work-as-done) in a health information technology-enabled emergency department setting. The objectives were to identify (1) variations in work-as-done in test results management and (2) the strategies clinicians use to ensure optimal management of diagnostic test results.

To mine Twitter and quantitatively analyze COVID-19 symptoms self-reported by users, compare symptom distributions across studies, and create a symptom lexicon for future research.

The study sought to evaluate the overall performance of hospitals that used the Computerized Physician Order Entry Evaluation Tool in both 2017 and 2018, along with their performance against fatal orders and nuisance orders.

The study sought to evaluate early lessons from a remote patient monitoring engagement and education technology solution for patients with coronavirus disease 2019 (COVID-19) symptoms.

We introduce fold-stratified cross-validation, a validation methodology that is compatible with privacy-preserving federated learning and that prevents data leakage caused by duplicates of electronic health records (EHRs).

As coronavirus disease 2019 (COVID-19) started its rapid emergence and gradually transformed into an unprecedented pandemic, the need for having a knowledge repository for the disease became crucial. To address this issue, a new COVID-19 machine-readable dataset known as the COVID-19 Open Research Dataset (CORD-19) has been released. Based on this, our objective was to build a computable co-occurrence network embeddings to assist association detection among COVID-19-related biomedical entities.

The study sought to describe the development, implementation, and requirements of laboratory information system (LIS) functionality to manage test ordering, registration, sample flow, and result reporting during the coronavirus disease 2019 (COVID-19) pandemic.

In 2009, a prominent national report stated that 9% of US hospitals had adopted a "basic" electronic health record (EHR) system. This statistic was widely cited and became a memetic anchor point for EHR adoption at the dawn of HITECH. However, its calculation relies on specific treatment of the data; alternative approaches may have led to a different sense of US hospitals' EHR adoption and different subsequent public policy.